Applications of AI in Industrial Safety and Occupational Health Risk Management

Abstract 

The rapid growth of the Artificial Intelligence (AI) has largely altered the practices of risk management of industrial safety and occupational health and safety (OHS). Construction, mining, oil and gas, manufacturing, transportation, and the maritime industries are the other industries that are progressively using AI based technologies in an effort to enhance hazard detection, risk forecasts, real-time surveillance and decision-making. The paper provides a literature review of AI application in industrial safety and risk management, identifies the major technologies, advantages, limitations, and perspectives. The review summarizes the results of the latest publications dated 2018-25, and the tools of AI that are discussed include machine learning, deep neural networks, computer vision, sensor networks, and predictive analytics. Although AI has a high potential of being proactive in preventing risks and efficient in its operations, there are several technical and ethical, legal and organizational challenges to consider. This research can be summarized as to find a middle ground in the application of AI, which is regulated and balanced and has explainable and reliable systems, is needed to provide sustainable and safe industrial implementation. 

Keywords: Artificial Intelligence, Industrial Safety, Occupational Health and Safety, Risk Management, Machine Learning, Predictive Safety